PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

John VerWey, an advisor in the Mission Alignment group at PNNL, has recently been selected to lead a panel discussion at the inaugural Special Competitive Studies Project (SCSP) AI+ Compute & Connectivity Summit.

The Resilience Analysis Specialty Group is part of the Society for Risk Analysis, the premier international society for risk analysis professionals.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

PNNL's “co-scientist” serves as a one-stop AI shop for accelerating scientific discovery. By leveraging AI agents, researchers can explore scientific databases, conduct analyses and request step-by-step plans for testing their hypotheses.

Researchers can now quantify uncertainty in trained AI models aimed at solving difficult chemistry, biology and materials science problems.

By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.

CACTUS provides AI-powered cheminformatics for autonomous science.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

A new generation of microelectronics research begins at PNNL.

His expertise in data science and commitment to open science will drive dataset dissemination and advance collaborative global research efforts.

Federal environmental permitting process to be fast-tracked with AI-powered tools and cloud-supported data analysis.

Samrat Chatterjee will serve on the editorial board of Risk Analysis, the flagship journal of the Society for Risk Analysis.

PNNL researchers work with industry partners to transform large language models.

University of Washington Professor David Baker won the 2024 Nobel Prize in Chemistry for computational protein design.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

Samrat (Sam) Chatterjee, a PNNL chief data scientist and team leader with the Data Sciences and Machine Intelligence group, was co-author of a CSET workshop report on agentic artificial intellilligence